Predictors of relapse in Takayasu arteritis

医学 内科学 血管炎 比例危险模型 动脉炎 队列 前瞻性队列研究 巨细胞动脉炎 心脏病学 胃肠病学 疾病
作者
Shiping He,Ruofan Li,Shangyi Jin,Yanhong Wang,Hongbin Li,Xinwang Duan,Lili Pan,Lijun Wu,Yongfu Wang,Yan Zhang,Zhenbiao Wu,Jing Li,Yunjiao Yang,Xinping Tian,Xiaofeng Zeng
出处
期刊:European Journal of Internal Medicine [Elsevier BV]
标识
DOI:10.1016/j.ejim.2023.02.027
摘要

Takayasu arteritis (TAK) is a large-vessel vasculitis with high relapse rate. Longitudinal studies identifying risk factors of relapse are limited. We aimed to analyze the associated factors and develop a risk prediction model for relapse.We analyzed the associated factors for relapse in a prospective cohort of 549 TAK patients from the Chinese Registry of Systemic Vasculitis cohort between June 2014 and December 2021 using univariate and multivariate Cox regression analyses. We also developed a prediction model for relapse, and stratified patients into low-, medium-, and high-risk groups. Discrimination and calibration were measured using C-index and calibration plots.At a median follow-up of 44 (IQR 26-62) months, 276 (50.3%) patients experienced relapses. History of relapse (HR 2.78 [2.14-3.60]), disease duration <24 months (HR 1.78 [1.37-2.32]), history of cerebrovascular events (HR 1.55 [1.12-2.16]), aneurysm (HR 1.49 [1.10-2.04], ascending aorta or aortic arch involvement (HR 1.37 [1.05-1.79]), elevated high-sensitivity C-reactive protein level (HR 1.34 [1.03-1.73]), elevated white blood cell count (HR 1.32 [1.03-1.69]), and the number of involved arteries ≥6 (HR 1.31 [1.00-1.72]) at baseline independently increased the risk of relapse and were included in the prediction model. The C-index of the prediction model was 0.70 (95% CI 0.67-0.74). Predictions correlated with observed outcomes on the calibration plots. Compared to the low-risk group, both medium and high-risk groups had a significantly higher relapse risk.Disease relapse is common in TAK patients. This prediction model may help to identify high-risk patients for relapse and assist clinical decision-making.
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